Study: Food poisoning bacteria can now be detected by Computers

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The most dangerous strains of E. coli O157 could be very rare in cattle, according to new research that used a computer to predict strains of bacteria that are likely to cause food poisoning outbreaks.

 

A study, led by the University of Edinburgh’s Roslin Institute and published in the Proceedings of the National Academy of Sciences, has shown that data analytics and artificial intelligence can predict which bacterial strains commonly found in cattle could spread to people.

 

The study could help public health officials target interventions and reduce risk to human health.

 

Researchers of the Institute used software that compares genetic information from bacterial samples isolated from both animals and people. The software learns the DNA signatures that are associated with E. coli samples that have caused outbreaks of infection in people. It can then pick out the animal strains that have these signatures, which are therefore likely to be a threat to human health.
Cows are the main reservoir of these toxic bacteria, which are linked to serious human infections. A recent outbreak in Scotland – which is thought to have originated from unpasteurized cheese – led to the death of a child and 19 further cases of serious food poisoning.

 

Using this approach, the team predicts that less than 10 percent of the E Coli O157 cattle strains are likely to have the potential to cause human disease.

 

E. Coli bacteria can cause stomach cramps, vomiting and diarrhoea.

 

The technique might also prove useful for other types of bacteria isolated from animals, such as Salmonella and Campylobacter. These are common causes of the more than 500,000 cases of food poisoning in the UK every year, according to the Food Standards Agency.

 

The study, funded by Food Standards Scotland and the Food Standards Agency, is published in the Proceedings of the National Academy of Sciences.

 

 

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